Simulation And Intelligent Optimizing Of Developing Process Of Weapon Equipment Under Uncertain Factors

The development level of weapon equipment is a significant sign of national defense, military strength and level of the scientific research, at the meantime, it's the concentrated reflection of comprehensive national power of a country, and moreover, it's an important guarantee of the security of national territory and national airspace. As is known, the design of weapon equipment is closely associated with multiple units, such as the military, the scientific research institutions and manufacturing department, meanwhile, the procedure is complex, which increases the difficulty of harmonized integration, therefore, risk analysis is of great significance to the development of weapon equipment. On the background of the development of weapon equipment, this paper, based on the design structure matrix(DSM) theory, does the research of simulated computation and intelligent optimization and reorganization with regard to the process of synergistic development under uncertain circumstances.Firstly, so as to attain the effect of quality control in the process, this paper adopts a method based on the quality feedback to describe rework of tasks, which could guarantee the completion quality of sub-tasks to satisfy the expected quality index; then by means of Monte Carlo simulation method the total time and total cost of the project can be obtained with computation. What is more, in the process of simulated computation, the relations of time, cost and quality are all taken into consideration, and the use of Cholesky factorization method realizes the simulation of related random variables, promoting the accuracy of simulation results.Secondly, it's the statistical analysis on the aforementioned computation results, which includes the schedule risk and cost risk of project, the fitting analysis of probability density curve on the total time and total cost and sensitivity analysis, which helps to identify the task that mostly influences the schedule risk and cost risk by the fluctuation of completion quality among all the sub-tasks. Besides, according to the mentioned study, this paper develops the initialization module on data and the analysis module on results.Thirdly, taking some objective and subjective factors into consideration, it's obviously that the data of the model will vary in a certain range, therefore, this paper adopts the interval grey number to represent the uncertainty of design structure matrix model. Specifically, the paper firstly establishes a suitable selection strategy that based on the order relation of interval grey number, and then uses the genetic algorithm to optimize and reorganize the process of manufacturing project with poor information. At last, through the comparison of the example verifying the effect of optimization, and further reducing the information feedback strength, schedule risk and cost risk of the project. Besides, this paper develops the intelligent optimization and reorganization module for the manufacturing process based on the aforementioned theory.Finally, for the sake that not only model for the collaborative-parallel process, but also express the rework modification of task itself, this paper puts in DSM-GERT hybrid model for the first time, which can exert the advantages of DSM and GERT network at the same time, embedding the complex DSM model into the GERT network. Simulation shows that this hybrid model can compute the parameter such as schedule, cost and risk degree in the course of a jet manufacturing process.